Critical care explorations最新文献

Context: Sepsis leads to multiple organ dysfunction and negatively impacts patient outcomes. Skeletal muscle disuse is a significant comorbidity in septic patients during their ICU stay due to prolonged immobilization.

Hypothesis: Combination of sepsis and muscle disuse will promote a unique proteomic signature in skeletal muscle in comparison to disuse and sepsis separately.

Methods and models: Following cecal ligation and puncture (CLP) or Sham surgeries, mice were subjected to hindlimb suspension (HLS) or maintained normal ambulation (NA). Tibialis anterior muscles from 24 C57BL6/J male mice were harvested for proteomic analysis. Proteomic profiles were assessed using nano-liquid chromatography with tandem mass spectrometry, followed by data analysis including Partial Least Squares Discriminant Analysis (PLS-DA), to compare the differential protein expression across groups.

Results: A total of 2876 differentially expressed proteins were identified, with marked differences between groups. In mice subjected to CLP and HLS combined, there was a distinctive proteomic signature characterized by a significant decrease in the expression of proteins involved in mitochondrial function and muscle metabolism, alongside a marked increase in proteins related to muscle degradation pathways. The PLS-DA demonstrated a clear separation among experimental groups, highlighting the unique profile of the CLP/HLS group. This suggests an important interaction between sepsis-induced inflammation and disuse atrophy mechanisms in sepsis-induced myopathy.

Interpretations and conclusions: Our findings reveal a complex proteomic landscape in skeletal muscle exposed to sepsis and disuse, consistent with an exacerbation of muscle protein degradation under these combined stressors. The identified proteins and their roles in cellular stress responses and muscle pathology provide potential targets for intervention to mitigate muscle dysfunction in septic conditions, highlighting the importance of addressing both sepsis and disuse concurrently in clinical and experimental settings.

Objectives background: This study aimed to assess the impact of race on pulse oximetry reliability, taking into account Spo₂ ranges, COVID-19 diagnosis, and ICU admission.

Design: Retrospective cohort study covering admissions from January 2020 to April 2024.

Setting: National COVID Cohort Collaborative (N3C) database, consisting of electronic health records from 80 U.S. institutions.

Patients/subjects: Patients were selected from the N3C database based on the availability of data on self-identified race and both pulse oximetry estimated Spo₂ and Sao₂. Subgroups included patients in ICU and non-ICU settings, with or without a diagnosis of COVID-19 disease.

Interventions: None.

Measurements and main results: The agreement between Spo₂ and Sao₂ was assessed across racial groups (American Indian or Alaska Native, Asian, Black, Hispanic or Latino, Pacific Islander, and White). Each patient's initial Sao₂ measurement was matched with the closest Spo₂ values recorded within the preceding 10-minute time frame. The risk of hidden hypoxemia (Spo₂ ≥ 88% but Sao₂ < 88%) was determined for various Spo₂ ranges, races, and clinical scenarios. We used a generalized logistic mixed-effects model to evaluate the impact of relevant variables, such as COVID-19, ICU admission, age, sex, race, and Spo₂, on the risk of hidden hypoxemia, while accounting for the random effects within each hospital. A total of 80,541 patients were included, consisting of 596 American Indian or Alaska Native, 2,729 Asian, 11,889 Black, 13,154 Hispanic or Latino, 221 Pacific Islander, and 51,952 White individuals. Discrepancies between Spo₂ and Sao₂ were observed across all racial groups, with the most pronounced bias in Black patients. Hidden hypoxemia rates were higher in Black patients across all Spo₂ subgroups, for all clinical scenarios. The odds of hidden hypoxemia were higher for Black and Hispanic or Latino patients and for those with COVID-19 disease.

Conclusions: Race significantly impacts pulse oximetry reliability. Not only Black and Hispanic or Latino patients were at higher risk for hidden hypoxemia, but also those admitted with a COVID-19 diagnosis. Future in-depth explorations into the underlying causes and potential solutions are needed.

Importance: In-hospital cardiac arrest (IHCA) is a significant public health burden. Rates of return of spontaneous circulation (ROSC) have been improving, but the best way to care for patients after the initial resuscitation remains poorly understood, and improvements in survival to discharge are stagnant. Existing North American cardiac arrest databases lack comprehensive data on the postresuscitation period, and we do not know current post-IHCA practice patterns. To address this gap, we developed the Discover IHCA study, which will thoroughly evaluate current post-IHCA care practices across a diverse cohort.

Objectives: Our study collects granular data on post-IHCA treatment practices, focusing on temperature control and prognostication, with the objective of describing variation in current post-IHCA practices.

Design, setting, and participants: This is a multicenter, prospectively collected, observational cohort study of patients who have suffered IHCA and have been successfully resuscitated (achieved ROSC). There are 24 enrolling hospital systems (23 in the United States) with 69 individuals enrolling in hospitals (39 in the United States). We developed a standardized data dictionary, and data collection began in October 2023, with a projected 1000 total enrollments. Discover IHCA is endorsed by the Society of Critical Care Medicine.

Main outcomes and measures: The study collects data on patient characteristics, including prearrest frailty, arrest characteristics, and detailed information on postarrest practices and outcomes. Data collection on post-IHCA practice was structured around current American Heart Association and European Resuscitation Council guidelines. Among other data elements, the study captures postarrest temperature control interventions and postarrest prognostication methods.

Results: The majority of participating hospital systems are large, academic, tertiary care centers serving urban populations. The analysis will evaluate variations in practice and their association with mortality and neurologic function.

Conclusions and relevance: We expect this study, Discover IHCA, to identify variability in practice and outcomes following IHCA and be a vital resource for future investigations into best practices for managing patients after IHCA.

Background: Surrogates, proxies, and clinicians making shared treatment decisions for patients who have lost decision-making capacity often fail to honor patients' wishes, due to stress, time pressures, misunderstanding patient values, and projecting personal biases. Advance directives intend to align care with patient values but are limited by low completion rates and application to only a subset of medical decisions. Here, we investigate the potential of large language models (LLMs) to incorporate patient values in supporting critical care clinical decision-making for incapacitated patients in a proof-of-concept study.

Methods: We simulated text-based scenarios for 50 decisionally incapacitated patients for whom a medical condition required imminent clinical decisions regarding specific interventions. For each patient, we also simulated five unique value profiles captured using alternative formats: numeric ranking questionnaires, text-based questionnaires, and free-text narratives. We used pre-trained generative LLMs for two tasks: 1) text extraction of the treatments under consideration and 2) prompt-based question-answering to generate a recommendation in response to the scenario information, extracted treatment, and patient value profiles. Model outputs were compared with adjudications by three domain experts who independently evaluated each scenario and decision.

Results and conclusions: Automated extractions of the treatment in question were accurate for 88% (n = 44/50) of scenarios. LLM treatment recommendations received an average Likert score by the adjudicators of 3.92 of 5.00 (five being best) across all patients for being medically plausible and reasonable treatment recommendations, and 3.58 of 5.00 for reflecting the documented values of the patient. Scores were highest when patient values were captured as short, unstructured, and free-text narratives based on simulated patient profiles. This proof-of-concept study demonstrates the potential for LLMs to function as support tools for surrogates, proxies, and clinicians aiming to honor the wishes and values of decisionally incapacitated patients.

Objective: Mean arterial pressure (MAP) plays a significant role in regulating tissue perfusion and urine output (UO). The optimal MAP target in critically ill patients remains a subject of debate. We aimed to explore the relationship between MAP and UO.

Design: A retrospective observational study.

Setting: A general ICU in a tertiary medical center.

Patients: All critically ill patients admitted to the ICU for more than 10 hours.

Interventions: None.

Measurements and main results: MAP values and hourly UO were collected in 5,207 patients. MAP levels were categorized into 10 groups of 5 mm Hg (from MAP < 60 mm Hg to MAP > 100 mg Hg), and 656,423 coupled hourly mean MAP and UO measurements were analyzed. Additionally, we compared the UO of individual patients in each MAP group with or without norepinephrine (NE) support or diuretics, as well as in patients with acute kidney injury (AKI).Hourly UO rose incrementally between MAP values of 65-100 mm Hg. Among 2,226 patients treated with NE infusion, mean UO was significantly lower in the MAP less than 60 mm Hg group (53.4 mL/hr; 95% CI, 49.3-57.5) compared with all other groups (p < 0.001), but no differences were found between groups of 75 less than or equal to MAP. Among 2500 patients with AKI, there was a linear increase in average UO from the MAP less than 60 mm Hg group (57.1 mL/hr; 95% CI, 54.2-60.0) to the group with MAP greater than or equal to 100 mm Hg (89.4 mL/hr; 95% CI, 85.7-93.1). When MAP was greater than or equal to 65 mm Hg, we observed a statistically significant trend of increased UO in periods without NE infusion.

Conclusions: Our analysis revealed a linear correlation between MAP and UO within the range of 65-100 mm Hg, also observed in the subgroup of patients treated with NE or diuretics and in those with AKI. These findings highlight the importance of tissue perfusion to the maintenance of diuresis and achieving adequate fluid balance in critically ill patients.

Objective: Evaluate the consistency and clinical impact of standardized multimodality neuromonitoring (MNM) interpretation and reporting within a system of care for patients with severe traumatic brain injury (sTBI).

Design: Retrospective, observational historical case-control study.

Setting: Single-center academic level I trauma center.

Interventions: Standardized interpretation of MNM data summarized within daily reports.

Measurements main results: Consecutive patients with sTBI undergoing MNM were included. Historical controls were patients monitored before implementation of standardized MNM interpretation; cases were defined as patients with available MNM interpretative reports. Patient characteristics, physiologic data, and clinical outcomes were recorded, and clinical MNM reporting elements were abstracted. The primary outcome was the Glasgow Outcome Scale score 3-6 months postinjury. One hundred twenty-nine patients were included (age 42 ± 18 yr, 82% men); 45 (35%) patients were monitored before standardized MNM interpretation and reporting, and 84 (65%) patients were monitored after that. Patients undergoing standardized interpretative reporting received fewer hyperosmotic agents (3 [1-6] vs. 6 [1-8]; p = 0.04) and spent less time above an intracranial threshold of 22 mm Hg (22% ± 26% vs. 28% ± 24%; p = 0.05). The MNM interpretation cohort had a lower proportion of anesthetic days (48% [24-70%] vs. 67% [33-91%]; p = 0.02) and higher average end-tidal carbon dioxide during monitoring (34 ± 6 mm Hg vs. 32 ± 6 mm Hg; p < 0.01; d = 0.36). After controlling for injury severity, patients undergoing standardized MNM interpretation and reporting had an odds of 1.5 (95% CI, 1.37-1.59) for better outcomes.

Conclusions: Standardized interpretation and reporting of MNM data are a novel approach to provide clinical insight and to guide individualized critical care. In patients with sTBI, independent MNM interpretation and communication to bedside clinical care teams may result in improved intracranial pressure control, fewer medical interventions, and changes in ventilatory management. In this study, the implementation of a system for management, including standardized MNM interpretation, was associated with a significant improvement in outcome.

Objectives: Optimal timing of tracheostomy in severe traumatic brain injury (TBI) is unknown due to lack of clinical trials. We emulated a target trial to estimate the effect of early vs. delayed tracheostomy strategy on functional outcome of patients with severe TBI.

Design: Target trial emulation using 1:1 balanced risk-set matching.

Setting: North American hospitals participating in the TBI Hypertonic Saline randomized controlled trial of the Resuscitation Outcomes Consortium.

Patients: The prematching population consisted of patients with TBI and admission Glasgow Coma Scale less than or equal to 8, who were alive and on mechanical ventilation on the fourth day following trial enrollment, and stayed in the ICU for at least 5 days. Patients with absolute indication for tracheostomy and patients who died during the first 28 days with a decision to withdraw care were excluded.

Interventions: We matched patients who received tracheostomy at a certain timepoint (early group) with patients who had not received tracheostomy at the same timepoint but were at-risk of tracheostomy in the future (delayed group). The primary outcome was a poor 6-month functional outcome, defined as Glasgow Outcome Scale-Extended less than or equal to 4.

Measurements and main results: Out of 1282 patients available for analysis, 275 comprised the prematching population, with 75 pairs being created postmatching. Median time of tracheostomy differed significantly in the early vs. the delayed group (7.0 d [6.0-10.0 d] vs. 12.0 d [9.8-18.3 d]; p < 0.001). Only 40% of patients in the delayed group received tracheostomy. There was no statistically significant difference between groups regarding poor 6-month functional outcome (early: 68.0% vs. delayed: 72.0%; p = 0.593).

Conclusions: In a target trial emulation, early as opposed to delayed tracheostomy strategy was not associated with differences in 6-month functional outcome following severe TBI. Considering the limitations of target trial emulations, delaying tracheostomy through a "watchful waiting" approach may be appropriate.

Importance: Pediatric acute kidney injury (AKI) is a prevalent and morbid complication of shock. Its pathogenesis and early identification remain elusive.

Objectives: We aim to determine whether renal blood flow (RBF) measurements by point-of-care ultrasound (POCUS) and renin-angiotensin-aldosterone system (RAAS) hormones in pediatric shock associate with vasoactive requirements and AKI.

Design, setting, and participants: This is a single-center prospective, noninterventional observational cohort study in one tertiary PICU in North American from 2020 to 2022 that enrolled children younger than 18 years with shock without preexisting end-stage renal disease.

Main outcomes and measures: RBF was measured by POCUS on hospital days 1 and 3 and plasma RAAS hormone levels were measured on day 1. The primary outcome was the presence of AKI by Kidney Disease Improving Global Outcomes criteria at first ultrasound with key secondary outcomes of creatinine, blood urea nitrogen (BUN), Vasoactive-Inotrope Score (VIS), and norepinephrine equivalent dosing (NED) 48 hours after first ultrasound.

Results: Fifty patients were recruited (20 with AKI, mean age 10.5 yr, 48% female). POCUS RBF showed lower qualitative blood flow (power Doppler ultrasound [PDU] score) and higher regional vascular resistance (renal resistive index [RRI]) in children with AKI (p = 0.017 and p = 0.0007). Renin and aldosterone levels were higher in the AKI cohort (p = 0.003 and p = 0.007). Admission RRI and PDU associated with higher day 3 VIS and NED after adjusting for age, day 1 VIS, and RAAS hormones. Admission renin associated with higher day 3 creatinine and BUN after adjusting for age, day 1 VIS, and the ultrasound parameters.

Conclusions and relevance: In pediatric shock, kidney blood flow was abnormal and renin and aldosterone were elevated in those with AKI. Kidney blood flow abnormalities are independently associated with future cardiovascular dysfunction; renin elevations are independently associated with future kidney dysfunction. Kidney blood flow by POCUS may identify children who will have persistent as opposed to resolving AKI. RAAS perturbations may drive AKI in pediatric shock.

Importance and objectives: To compare the 18-month survival between patients with newly diagnosed cancer discharged home after early unplanned ICU admission and those without early unplanned ICU admission; we also evaluated the frequency and risk factors for early unplanned ICU admission.

Design: Observational study with prospectively collected data from September 2019 to June 2021 and 18 months follow-up.

Setting: Single dedicated cancer center in São Paulo, Brazil.

Participants: We screened consecutive adults with suspected cancer and included those with histologically proven cancer from among 20 highly prevalent cancers.

Interventions: None.

Measurements and main results: The exposure was early unplanned ICU admission, defined as admission for medical reasons or urgent surgery during the first 6 months after cancer diagnosis. The main outcome was 18-month survival after cancer diagnosis, and the main analysis was Cox's proportional hazards model adjusted for confounders and immortal time bias. Propensity score matching was used in the sensitivity analysis. We screened 4738 consecutive adults with suspected cancer and included 3348 patients. Three hundred twelve (9.3%) had early unplanned ICU admission, which was associated with decreased 18-month survival both in the unadjusted (hazard ratio, 4.03; 95% CI, 2.89-5.62) and adjusted (hazard ratio, 1.84; 95% CI, 1.29-2.64) models. The sensitivity analysis confirmed the results because the groups were balanced after matching, and the 18-month survival of patients with early ICU admission was lower compared with patients without early ICU admission (87.0% vs. 93.9%; p = 0.01 log-rank test). Risk factors for early unplanned ICU admission were advanced age, comorbidities, worse performance status, socioeconomic deprivation, metastatic tumors, and hematologic malignancies.

Conclusions: Patients with newly diagnosed cancer discharged home after early unplanned ICU admission have decreased 18-month survival compared with patients without early unplanned ICU admission.

Objectives: To identify interprofessional staffing pattern clusters used in U.S. ICUs.

Design: Latent class analysis.

Setting and participants: Adult U.S. ICUs.

Patients: None.

Interventions: None.

Analysis: We used data from a staffing survey that queried respondents (n = 596 ICUs) on provider (intensivist and nonintensivist), nursing, respiratory therapist, and clinical pharmacist availability and roles. We used latent class analysis to identify clusters describing interprofessional staffing patterns and then compared ICU and hospital characteristics across clusters.

Measurements and main results: We identified three clusters as optimal. Most ICUs (54.2%) were in cluster 1 ("higher overall staffing") characterized by a higher likelihood of good provider coverage (both intensivist [onsite 24 hr/d] and nonintensivist [orders placed by ICU team exclusively, presence of advanced practice providers, and physicians-in-training]), nursing leadership (presence of charge nurse, nurse educators, and managers), and bedside nursing support (nurses with registered nursing degrees, fewer patients per nurse, and nursing aide availability). One-third (33.7%) were in cluster 2 ("lower intensivist coverage & nursing leadership, higher bedside nursing support") and 12.1% were in cluster 3 ("higher provider coverage & nursing leadership, lower bedside nursing support"). Clinical pharmacists were more common in cluster 1 (99.4%), but present in greater than 85% of all ICUs; respiratory therapists were nearly universal. Cluster 1 ICUs were larger (median 20 beds vs. 15 and 17 in clusters 2 and 3, respectively; p < 0.001), and in larger (> 250 beds: 80.6% vs. 66.1% and 48.5%; p < 0.001), not-for-profit (75.9% vs. 69.4% and 60.3%; p < 0.001) hospitals. Telemedicine use 24 hr/d was more common in cluster 3 units (71.8% vs. 11.7% and 14.1%; p < 0.001).

Conclusions: More than half of U.S. ICUs had higher staffing overall. Others tended to have either higher provider presence and nursing leadership or higher bedside nursing support, but not both.